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Purpose: Practitioners in China who implement hospice care services include doctors, nurses, and care workers. These individuals play an important role in the holistic care of patients at the end of life and their families. This study aimed to provide baseline data to develop hospice care services and improve relevant policies by investigating the knowledge and attitudes of hospice care practitioners (HCPs) and analyzing influencing factors. Methods: This cross-sectional descriptive study used stratified sampling and quota sampling. The HCPs were from nursing homes, medical institutions, integrated medical and nursing institutions, and community health service centers in Guangxi Zhuang Autonomous Region. We examined HCPs' demographic characteristics and scores on a self-designed Chinese scale to measure their knowledge and attitudes(K&A scale). A total of 1821 HCPs completed surveys from May 2022 to July 2022. The data were analyzed using descriptive statistics, univariate analysis and multiple linear regression. Results: The standard score of the K&A scale of 1821 HCPs was 61.62 (SD=9.78), and the individual mean scores of knowledge and attitudes were 76.42 (SD=28.13) and 58.69 (SD=11.31), respectively. The final multiple linear regression analysis indicated that the main factors that influenced the K&A score were monthly income, job satisfaction, and the hospice care-related system (HCS). Conclusion: The HCPs in this study displayed moderate mean scores for knowledge and a less favorable attitude toward hospice care. Monthly income, job satisfaction and the HCS were the common factors that influenced HCPs' K&A. The results suggest the need to strengthen targeted and professional training for HCPs, increase their welfare and benefits, and improve indigenous policies of hospice care.
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Objective: This study aimed to develop and validate an assessment tool for predicting and mitigating the risk of frailty in patients diagnosed with hematologic malignancies. Methods: A total of 342 patients with hematologic malignancies participated in this study, providing data on various demographics, disease-related information, daily activities, nutritional status, psychological well-being, frailty assessments, and laboratory indicators. The participants were randomly divided into training and validation groups at a 7:3 ratio. We employed Lasso regression analysis and cross-validation techniques to identify predictive factors. Subsequently, a nomogram prediction model was developed using multivariable logistic regression analysis. Discrimination ability, accuracy, and clinical utility were assessed through receiver operating characteristic (ROC) curves, C-index, calibration curves, and decision curve analysis (DCA). Results: Seven predictors, namely disease duration of 6-12 months, disease duration exceeding 12 months, Charlson Comorbidity Index (CCI), prealbumin levels, hemoglobin levels, Generalized Anxiety Disorder-7 (GAD-7) scores, and Patient Health Questionnaire-9 (PHQ-9) scores, were identified as influential factors for frailty through Lasso regression analysis. The area under the ROC curve was 0.893 for the training set and 0.891 for the validation set. The Hosmer-Lemeshow goodness-of-fit test confirmed a good model fit. The C-index values for the training and validation sets were 0.889 and 0.811, respectively. The DCA curve illustrated a higher net benefit when using the nomogram prediction model within patients threshold probabilities ranging from 10% to 98%. Conclusions: This study has successfully developed and validated an effective nomogram model for predicting frailty in patients diagnosed with hematologic malignancies. The model incorporates disease duration (6-12 months and>12 months), CCI, prealbumin and hemoglobin levels, GAD-7, and PHQ-9 scores as predictive variables.
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Lasioderma serricorne, also known as cigarette beetle, can exploit a wide variety of stored materials as foods, but it is particularly common on tobacco and herbs. This beetle is a dominant pest species of stored Chinese medicinal materials (CMMs) causing high economic damages, making effective control strategies urgently needed. Behavioural manipulation is an important component of Integrated Pest Management. To the best of our knowledge, plant-borne volatile organic compounds (VOCs) have never been explored to develop lures for managing L. serricorne. In this study, the behavioural responses of L. serricorne to VOCs from four selected CMMs (Euphorbia kansui, Aconitum carmichaelii, Eucommia ulmoides and Pinellia ternata) were studied and their components analysed. Then, the olfactory responses of L. serricorne to the most abundant VOC identified in the preferred CMM, i.e., paeonal, was tested. L. serricorne showed significant differences in its preferences for the VOCs from the four CMMs, i.e, E. kansui > A. carmichaelii > E. ulmoides > P. ternata. From the VOCs of E. kansui, A. carmichaelii, E. ulmoides, and P. ternata, 77, 74, 56, and 81 molecules, were identified, respectively. Paeonal (23.5%), junipene (17.2%), hexanal (17.1%), and benzeneacetonitrile (14.0%) were the most abundant, respectively. Since paeonal dominated the VOC spectrum of the most preferred CMM, this compound was selected for further studies. L. serricorne showed significant positive responses to paeonal tested at various doses, with the most attractive ones being 100 µg and 500 µg. Our findings shed light on the olfactory cues routing the food searching behaviour in the cigarette beetle, providing important information on how L. serricorne targets particular CMMs. The high attractiveness of paeonal at low doses tested here may be exploited further to develop novel monitoring and control tools (e.g., lure-and-kill strategies) against this important stored product pest.
